Efficient detection of image blur and its extent is an open research problem in computer vision. Image blur has a negative impact on image quality. Blur is introduced into images due to various factors including limited contrast, improper exposure time or unstable device handling. Toward this end, an algorithm is presented for image blur detection with the use of Two-Dimensional Haar Wavelet transform (2D HWT). The algorithm is experimentally compared with two other image blur detection algorithms frequently cited in the literature. When evaluated over a sample of images, the algorithm performed on par or better than the two other blur detection algorithms.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-5483 |
| Date | 01 August 2015 |
| Creators | Andhavarapu, Sarat Kiran |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu). |
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